AI process automation where it hurts the most.
Explore automation by your department, your industry, or your objective. Each solution is a specific process, not a vague promise.
Our approach
Automation doesn't start with a tool. It starts with a process.
Most AI automation projects fail because a technology is chosen first, and only then is a use case sought for it. The result is a chatbot nobody uses or a script that breaks at the first exception to the rule.
We do it the other way around. We map how a process actually runs — not how it's documented — find the steps where the most time is lost, and only then do we automate them. It often turns out that simply cleaning up the process delivers half the savings, and AI provides the other half.
AI agents then run inside your system: they read data, write data, and hand off work to each other, leaving an audit trail at every step. When they're unsure, they escalate to a human instead of guessing.
Solutions overview
Find your path below.
One system, three perspectives. Choose the one that matches how you think about the problem.
Solutions by department
Solutions by industry
Solutions by goal
What you get
Not a presentation, but a running process.
Deployment within 30 days
We don't start with a six-month analysis project. The first process is live in production within a month, we measure its real-world impact, and only then do we expand to others.
Control at every step
You can see what an agent did, why it did it, and what data it used. You can set critical steps to require human approval — automation doesn't mean losing oversight.
We calculate the return upfront
Before we build anything, we calculate how many hours the process costs each month and how many of those we can realistically save. If the numbers don't add up, we'll tell you, and we won't build it.
Frequently asked questions
Before you decide.
For what size of company does AI automation make sense?
The deciding factor isn't the number of people, but the volume of repetitive work. If someone in the company spends more than five hours a week re-entering data between systems, searching through emails, or assembling the same documents, the return on investment is usually within six months.
Will AI replace our people?
In practice, it takes over their routine tasks, not their jobs. An agent prepares a document, a quote, or a report, and a person reviews it and makes the decision. The companies we work with don't usually lay people off after deployment — they just handle more work with the same team.
Do we need to have our data in order first?
No, but we need to know where the mess is. A data audit is part of the process mapping. Sometimes it turns out the first step isn't AI, but unifying your code lists — and we'll tell you that upfront.
How do you handle security and GDPR?
We process data on European infrastructure, access is role-based, and every agent action is logged. We provide a data processing agreement and a description of data flows as part of the deployment.
What if we already have some automations in place?
We'll build on them. We commonly take over existing scenarios in Make or n8n and connect them to the system, so they stop being isolated islands with no oversight or error reporting.
How much does it cost and how is it paid?
A one-off deployment fee based on the scope of the process, then a monthly subscription starting from 4,990 CZK. We'll quote the deployment price only after the mapping phase — otherwise, it would be an estimate, not a firm offer.
Next step
Tell us what's slowing you down the most.
In a half-hour call, we'll walk through one of your processes and tell you if automation is worthwhile, how much it could save, and what the deployment would entail.